NAND flash memory is a widely used storage medium that can be treated as a noisy channel. Each flash memory cell stores data as the threshold voltage of a floating gate transistor. The threshold voltage can shift as a result of various types of circuit-level noise, introducing errors when data are read from the channel and ultimately reducing flash lifetime. An accurate model of the threshold volt...
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The beta-binomial (BBM) channel model was recently proposed to model the overdispersed statistics of empirically observed bit errors in multi-level cell (MLC) flash memories. In this paper, we study the capacity of the BBM channel model for MLC flash memories. Using the compound channel approach, we first show that the BBM channel model capacity is zero. However, through empirical observation, thi...
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In the write process of multilevel per cell (MLC) flash memories, an iterative approach is used to mitigate the monotonicity problem. The monotonicity in programming is considered to be the major restriction in MLC flash. To solve this issue, an iterative approach called incremental step pulse programming (ISPP) is used to concurrently program lots of cells in small steps. In this paper, we are mo...
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In this paper, we study the performance of different decoding schemes for multilevel flash memories where each page in every block is encoded independently. We focus on multi-level cell flash memory, which is modeled as a two-user multiple-access channel suffering from asymmetric noise. The uniform rate regions and sum rates of treating interference as noise decoding and successive cancelation dec...
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In this paper, we develop a framework for evaluating the symmetric capacity of multilevel-cell (MLC) NAND flash devices while making very few assumptions regarding the underlying device physics. A set of recursive equations are derived that allow one to measure the symmetric capacity for any given page in a flash device using simple conditional statistics that can be extracted experimentally. Usin...
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We propose using variable-length constrained sequence codes to mitigate inter-cell interference (ICI) in all-bit-line flash memory with multi-page programming for single-level cell, multi-level cell, and triple-level cell flash memory structures. We outline constraints that mitigate ICI in these systems based on an observation of the Gray mapping of data symbols, and we derive the capacity of each...
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In recent years, due to the spread of multi-level nonvolatile memories (NVMs), q-ary write-once memory (WOM) codes have been extensively studied. By using WOM codes, it is possible to rewrite NVMs t times before erasing the cells. Use of WOM codes enables the improvement of the performance of the storage device; however, it may also increase errors caused by inter-cell interference (ICI). This pap...
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For low-density parity-check (LDPC) codes widely used in NAND flash memories, the bit-error rate performance is closely tied to the number of bits per message used by the message-passing decoder. This paper describes a technique to generate message-passing decoding mapping functions for LDPC codes using 3 and 4 bits per message. These maps are not derived from belief-propagation decoding or one of...
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In multi-level-cell memory, such as flash and phase-change memory, shrinking cell size and the growing number of levels per cell worsen the access rate to capacity ratio and even reduce access rate. We present minimal maximum-level programming, a scheme for expediting cell programming by sharing physical cells among multiple data sectors and exploiting the fact that making moderate changes to a ce...
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The discrete-grains model is a simple model for the distribution of “grains” on a magnetic medium. In this model, grains on the medium are taken to be one of four basic rectangular shapes (“tiles”)-1 × 1, 1 × 2, 2 × 1, and 2 × 2. The magnetic medium is then modeled as an N × N square tiled by these four basic tiles. In this paper, we p...
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This paper considers turbo equalization for 2-D magnetic recording. Magnetic grains are modeled as Voronoi regions of randomly distributed nuclei. Bits read from the magnetic grain model flow into a 2-D intersymbol interference (2D-ISI) model including additive white Gaussian noise. At high bit densities, some bits are not written on any grain, and hence are effectively “overwritten”...
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Two-dimensional magnetic recording promises to increase areal density through the joint detection of multiple tracks of interest. This paper concerns the problem of joint detection of multiple tracks that are written asynchronously, meaning that neither the bit boundaries (phase) nor the bit rate (frequency) are aligned between neighboring tracks. We propose the rotating-target algorithm for joint...
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Resistive memories, such as phase change memories and resistive random access memories, have attracted significant research interest because of their scalability, non-volatility, fast speed, and rewritability. However, their write endurance needs to be improved substantially for large-scale deployment of resistive memories. In addition, their write power consumption is much higher than the power c...
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High-performance storage class memories could benefit from a fast decoding error correcting code (ECC), able to correct a few errors in just a few nanoseconds. The class of BCH codes provides excellent candidates to play this role. The low latency requirement prevents adopting iterative or sequential processes in the encoding and decoding phases-as traditionally done for storage application based ...
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We consider the transmission and storage of data that use coded binary symbols over a channel, where a Pearson distance-based detector is used for achieving resilience against additive noise, unknown channel gain, and varying offset. We study minimum Pearson distance (MPD) detection in conjunction with a set, S, of codewords satisfying a center-of-mass constraint. We investigate the properties of ...
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This paper proposes a noise-predictive detection algorithm for intersymbol interference channels with linear regressive noise. A block factorization of the covariance matrix of the linear regressive Gaussian noise is used to derive the branch metrics. This algorithm exhibits near optimal performance. A generalization of this algorithm to signal dependent linear regressive noise is also presented a...
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